Network perturbation analysis of gene transcriptional profiles reveals protein targets and mechanism of action of drugs and influenza A viral infection

Noh, Heeju; Shoemaker, Jason E; Gunawan, Rudiyanto

The identification of the molecular targets of pharmacologically relevant compounds is vital for understanding the mechanism of action (MoA) of drugs, as well as for exploring off-target effects. While the definition of a target can be quite arbitrary, the term generally refers to a molecule whose interaction with the compound is connected to the compound's effects (1) . In this study, transcription factors (TFs) and their protein interaction partners represent the target molecules, while differential gene expression profiles represent the effects. Among existing technologies for protein target discovery (e.g. biochemical affinity purification, RNAi knockdown or gene knockout experiments) (2) , gene expression profiling has received much recent attention due to its relative ease of implementation as well as the availability of large-scale public databases and well-established experimental protocols and data analytical methods. A complication when using gene expression profiling for target discovery is that the data give only indirect indications of the drug's action. As illustrated in Figure 1A , the interaction between a compound and its protein target(s) is expected to result in the differential expression of downstream genes that are regulated by the protein target(s). But, the expression of the protein targets themselves may not--and often do not--change (3) . Consequently, target discovery using gene expression profiles requires computational methods to identify the (upstream) targets from the (downstream) effects.